iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.1038/s44159-023-00224-6
Connecting spatial thinking to STEM learning through visualizations | Nature Reviews Psychology
Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Connecting spatial thinking to STEM learning through visualizations

Abstract

Spatial thinking relates to interest and success in science, technology, engineering and mathematics (STEM) disciplines. In this Review, we suggest that visualizations connect spatial and STEM thinking because all STEM disciplines use visualizations, and visualizations use space to meaningfully organize information. We focus on visualizations to show that their ubiquitous use reflects the importance of spatial thinking in STEM. In building to this point, we discuss different ways to think spatially, as spatial thinking is not a unitary process. With this base, we review the cognitive underpinnings of spatial thinking and visualization comprehension, including attention, perception and memory. We then examine how spatial thinking is involved when processing visualizations, across visualization types and STEM fields. We end by discussing future work to further probe the importance of visualizations and their connection to spatial thinking and STEM success.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The connection between spatial thinking, visualizations and STEM learning.
Fig. 2: Spatial tasks.
Fig. 3: Differences between iconic and relational visualizations.
Fig. 4: Sample iconic and relational diagrams across different science, technology, engineering and math fields.

Similar content being viewed by others

References

  1. Wai, J., Lubinski, D. & Benbow, C. P. Spatial ability for STEM domains: aligning over 50 years of cumulative psychological knowledge solidifies its importance. J. Educ. Psychol. 101, 817–835 (2009).

    Article  Google Scholar 

  2. Edsall, T. B. We are leaving ‘Lost Einsteins’ behind. New York Times (21 July 2021).

  3. Kell, H. J. & Lubinski, D. Spatial ability: a neglected talent in educational and occupational settings. Roeper Rev. 35, 219–230 (2013).

    Article  Google Scholar 

  4. Judd, N. & Klingberg, T. Training spatial cognition enhances mathematical learning in a randomized study of 17,000 children. Nat. Hum. Behav. 5, 1548–1554 (2021).

    Article  PubMed  Google Scholar 

  5. Buckley, J., Seery, N. & Canty, D. A heuristic framework of spatial ability: a review and synthesis of spatial factor literature to support its translation into STEM education. Educ. Psychol. Rev. 30, 947–972 (2018). This review analyses spatial and visual cognitive processes with relevance to STEM disciplines to expand the spatial factors represented in existing frameworks.

    Article  Google Scholar 

  6. Uttal, D. H. & Cohen, C. A. in Psychology of Learning and Motivation vol. 57 (ed. Ross, B. H.) 147–181 (Elsevier, 2012). This paper proposes that students’ strong or weak spatial skills serve as either a gateway or a barrier, respectively, for entry into STEM fields.

  7. Newcombe, N. S. & Shipley, T. F. in Studying Visual and Spatial Reasoning for Design Creativity (ed. Gero, J. S.) 179–192 (Springer, 2015).

  8. Uttal, D. H. et al. The malleability of spatial skills: a meta-analysis of training studies. Psychol. Bull. 139, 352–402 (2013). This meta-analysis finds that the magnitude of the impact of training of spatial thinking skills is moderate and sustained over time, suggesting that spatial thinking skills are moderately malleable and durable.

    Article  PubMed  Google Scholar 

  9. Stieff, M. & Uttal, D. How much can spatial training improve STEM achievement? Educ. Psychol. Rev. 27, 607–615 (2015). This review analyses correlational and longitudinal evidence that connects spatial thinking skills and STEM achievement and provides preliminary evidence of the effectiveness of spatial training.

    Article  Google Scholar 

  10. Sorby, S., Veurink, N. & Streiner, S. Does spatial skills instruction improve STEM outcomes? The answer is ‘yes’. Learn. Individ. Differ. 67, 209–222 (2018). This paper reports results of an intensive spatial skills intervention with engineering students and finds that the intervention resulted in better grades and had a positive impact on women’s retention rates in engineering.

    Article  Google Scholar 

  11. Newcombe, N. S. & Stieff, M. Six myths about spatial thinking. Int. J. Sci. Educ. 34, 955–971 (2012). This paper dispels myths about spatial thinking to redirect research efforts towards more productive investigations of best practices using visualizations in science education.

    Article  Google Scholar 

  12. Shea, D. L., Lubinski, D. & Benbow, C. P. Importance of assessing spatial ability in intellectually talented young adolescents: a 20-year longitudinal study. J. Educ. Psychol. 93, 604–614 (2001).

    Article  Google Scholar 

  13. Lubinski, D. & Benbow, C. P. Study of mathematically precocious youth after 35 years: uncovering antecedents for the development of math–science expertise. Perspect. Psychol. Sci. 1, 316–345 (2006).

    Article  PubMed  Google Scholar 

  14. Kell, H. J., Lubinski, D. & Benbow, C. P. Who rises to the top? Early indicators. Psychol. Sci. 24, 648–659 (2013).

    Article  PubMed  Google Scholar 

  15. Wai, J. & Kell, H. J. in Visual-spatial Ability in STEM Education (ed. Khine, M. S.) 109–124 (Springer, 2017).

  16. Hegarty, M. & Waller, D. A. in The Cambridge Handbook of Visuospatial Thinking (eds Shah, P. & Miyake, A.) 121–169 (Cambridge Univ. Press, 2005). This review overviews types of spatial thinking, individual differences in performance and the cognitive processes underlying spatial thinking skills that support STEM achievement.

  17. Hegarty, M. in Diagrammatic Representation and Inference (eds Blackwell, A. F., Marriott, K. & Shimojima, A.) 1–13 Lecture Notes in Computer Science series vol. 2980 (Springer, 2004).

  18. Munzner, T. Visualization Analysis and Design (A. K. Peters/CRC Press, 2014).

  19. Ivson, P., Moreira, A., Queiroz, F., Santos, W. & Celes, W. A systematic review of visualization in building information modeling. IEEE Trans. Vis. Comput. Graph. 26, 3109–3127 (2020).

    Article  PubMed  Google Scholar 

  20. Islam, M. & Jin, S. in 2019 International Conference on Information Science and Communications Technologies (ICISCT) https://doi.org/10.1109/ICISCT47635.2019.9012031 (IEEE, 2019).

  21. Evagorou, M., Erduran, S. & Mäntylä, T. The role of visual representations in scientific practices: from conceptual understanding and knowledge generation to ‘seeing’ how science works. Int. J. STEM Educ. 2, 11 (2015).

    Article  Google Scholar 

  22. Watson, J. D. & Stent, G. S. The Double Helix: A Personal Account of the Discovery of the Structure of DNA (Scribner, 1998).

  23. Liu, Y. & Khine, M. S. Content analysis of the diagrammatic representations of primary science textbooks. EURASIA J. Math. Sci. Technol. Educ. 12, 1937–1951 (2016).

    Google Scholar 

  24. Liu, Y. & Treagust, D. F. in Critical Analysis of Science Textbooks (ed. Khine, M. S.) 287–300 (Springer, 2013).

  25. National Research Council. A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas (National Academies Press, 2012).

  26. Singer, S. R., Nielsen, N. R. & Schweingruber, H. A. Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering (National Academies Press, 2012).

  27. LaDue, N. D., Libarkin, J. C. & Thomas, S. R. Visual representations on high school biology, chemistry, earth science, and physics assessments. J. Sci. Educ. Technol. 24, 818–834 (2015).

    Article  Google Scholar 

  28. Guo, D., McTigue, E. M., Matthews, S. D. & Zimmer, W. The impact of visual displays on learning across the disciplines: a systematic review. Educ. Psychol. Rev. 32, 627–656 (2020).

    Article  Google Scholar 

  29. Cromley, J. G., Snyder-Hogan, L. E. & Luciw-Dubas, U. A. Cognitive activities in complex science text and diagrams. Contemp. Educ. Psychol. 35, 59–74 (2010).

    Article  Google Scholar 

  30. Burte, H., Gardony, A. L., Hutton, A. & Taylor, H. A. Think3d!: improving mathematics learning through embodied spatial training. Cogn. Res. Princ. Implic. 2, 13 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Titus, S. & Horsman, E. Characterizing and improving spatial visualization skills. J. Geosci. Educ. 57, 242–254 (2009).

    Article  Google Scholar 

  32. Liu, Z. & Stasko, J. T. Mental models, visual reasoning and interaction in information visualization: a top-down perspective. IEEE Trans. Vis. Comput. Graph. 16, 999–1008 (2010).

    Article  PubMed  Google Scholar 

  33. Lohman, D. F., Pellegrino, J. W., Alderton, D. L. & Regian, J. W. in Intelligence and Cognition: Contemporary Frames of Reference (eds Irvine, S. H. & Newstead, S. E.) 253–312 (Springer, 1987).

  34. Carroll, J. B. Human Cognitive Abilities: A Survey of Factor-Analytic Studies (Cambridge Univ. Press, 2004).

  35. Hegarty, M. & Waller, D. A dissociation between mental rotation and perspective-taking spatial abilities. Intelligence 32, 175–191 (2004).

    Article  Google Scholar 

  36. Kozhevnikov, M. & Hegarty, M. A dissociation between object manipulation spatial ability and spatial orientation ability. Mem. Cognit. 29, 745–756 (2001).

    Article  PubMed  Google Scholar 

  37. National Research Council. Learning to Think Spatially (National Academies Press, 2006).

  38. Hodgkiss, A., Gilligan‐Lee, K. A., Thomas, M. S. C., Tolmie, A. K. & Farran, E. K. The developmental trajectories of spatial skills in middle childhood. Br. J. Dev. Psychol. 39, 566–583 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kozhevnikov, M., Kosslyn, S. & Shephard, J. Spatial versus object visualizers: a new characterization of visual cognitive style. Mem. Cognit. 33, 710–726 (2005).

    Article  PubMed  Google Scholar 

  40. Voyer, D., Voyer, S. & Bryden, M. P. Magnitude of sex differences in spatial abilities: a meta-analysis and consideration of critical variables. Psychol. Bull. 117, 250–270 (1995). This meta-analysis reveals that the magnitude of sex differences in spatial thinking depends on multiple variables and is diminishing over time.

    Article  PubMed  Google Scholar 

  41. Shepard, S. & Metzler, D. Mental rotation: effects of dimensionality of objects and type of task. J. Exp. Psychol. Hum. Percept. Perform. 14, 3–11 (1988).

    Article  PubMed  Google Scholar 

  42. Lauer, J. E., Yhang, E. & Lourenco, S. F. The development of gender differences in spatial reasoning: a meta-analytic review. Psychol. Bull. 145, 537–565 (2019).

    Article  PubMed  Google Scholar 

  43. Milivojevic, B., Johnson, B. W., Hamm, J. P. & Corballis, M. C. Non-identical neural mechanisms for two types of mental transformation: event-related potentials during mental rotation and mental paper folding. Neuropsychologia 41, 1345–1356 (2003).

    Article  PubMed  Google Scholar 

  44. Harris, J., Hirsh-Pasek, K. & Newcombe, N. S. Understanding spatial transformations: similarities and differences between mental rotation and mental folding. Cogn. Process. 14, 105–115 (2013).

    Article  PubMed  Google Scholar 

  45. Hegarty, M., Montello, D. R., Richardson, A. E., Ishikawa, T. & Lovelace, K. Spatial abilities at different scales: individual differences in aptitude-test performance and spatial-layout learning. Intelligence 34, 151–176 (2006).

    Article  Google Scholar 

  46. Bednarz, R. S. & Lee, J. The components of spatial thinking: empirical evidence. Procedia Soc. Behav. Sci. 21, 103–107 (2011).

    Article  Google Scholar 

  47. Burte, H., Gardony, A. L., Hutton, A. & Taylor, H. A. Elementary teachers’ attitudes and beliefs about spatial thinking and mathematics. Cogn. Res. Princ. Implic. 5, 17 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Newcombe, N. S. Thinking spatially in the science classroom. Curr. Opin. Behav. Sci. 10, 1–6 (2016).

    Article  Google Scholar 

  49. Atit, K., Uttal, D. H. & Stieff, M. Situating space: using a discipline-focused lens to examine spatial thinking skills. Cogn. Res. Princ. Implic. 5, 19 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Johnson-Laird, P. N. A theoretical analysis of insight into a reasoning task. Cognit. Psychol. 1, 134–148 (1970).

    Article  Google Scholar 

  51. Eliot, J., Macfarlane Smith, I. & Smith, I. M. An International Directory of Spatial Tests (NFER–Nelson, 1983).

  52. Karádi, K., Kállai, J. & Kovács, B. Cognitive subprocesses of mental rotation: why is a good rotator better than a poor one? Percept. Mot. Skills 93, 333–337 (2001).

    Article  PubMed  Google Scholar 

  53. Shepard, R. N. & Metzler, J. Mental rotation of three-dimensional objects. Science 171, 701–703 (1971).

    Article  PubMed  Google Scholar 

  54. Shepard, R. N. & Cooper, L. A. Mental Images and Their Transformations (MIT Press, 1982).

  55. Navon, D. Forest before trees: the precedence of global features in visual perception. Cognit. Psychol. 9, 353–383 (1977).

    Article  Google Scholar 

  56. Kimchi, R. Primacy of wholistic processing and global/local paradigm: a critical review. Psychol. Bull. 112, 24–38 (1992).

    Article  PubMed  Google Scholar 

  57. Boccia, M., Piccardi, L., Di Marco, M., Pizzamiglio, L. & Guariglia, C. Does field independence predict visuo-spatial abilities underpinning human navigation? Behavioural evidence. Exp. Brain Res. 234, 2799–2807 (2016).

    Article  PubMed  Google Scholar 

  58. Li, H., Zhang, Y., Wu, C. & Mei, D. Effects of field dependence-independence and frame of reference on navigation performance using multi-dimensional electronic maps. Personal. Individ. Differ. 97, 289–299 (2016).

    Article  Google Scholar 

  59. Golledge, R. G. in Cognitive Aspects of Human–Computer Interaction for Geographic Information Systems (eds Nyerges, T. L., Mark, D. M., Laurini, R. & Egenhofer, M. J.) 29–44 (Springer, 1995).

  60. Schendan, H. E. & Stern, C. E. Mental rotation and object categorization share a common network of prefrontal and dorsal and ventral regions of posterior cortex. NeuroImage 35, 1264–1277 (2007).

    Article  PubMed  Google Scholar 

  61. Peters, M. et al. A redrawn Vandenberg and Kuse mental rotations test - different versions and factors that affect performance. Brain Cogn. 28, 39–58 (1995).

    Article  PubMed  Google Scholar 

  62. Vandenberg, S. G. & Kuse, A. R. Mental rotations, a group test of three-dimensional spatial visualization. Percept. Mot. Skills 47, 599–604 (1978).

    Article  PubMed  Google Scholar 

  63. Ekstrom, R. B., French, J. W., Harman, H. & Derman, D. Kit of Factor-Referenced Cognitive Tests (revised edition) (Educational Testing Service, 1976).

  64. Bodner, G. M. & Guay, R. B. The Purdue Visualization of Rotations test. Chem. Educ. 2, 1–17 (1997).

    Article  Google Scholar 

  65. Bethell-Fox, C. E. & Shepard, R. N. Mental rotation: effects of stimulus complexity and familiarity. J. Exp. Psychol. Hum. Percept. Perform. 14, 12–23 (1988).

    Article  Google Scholar 

  66. Folk, M. D. & Luce, R. D. Effects of stimulus complexity on mental rotation rate of polygons. J. Exp. Psychol. Hum. Percept. Perform. 13, 395–404 (1987).

    Article  PubMed  Google Scholar 

  67. Jordan, K., Heinze, H.-J., Lutz, K., Kanowski, M. & Jäncke, L. Cortical activations during the mental rotation of different visual objects. NeuroImage 13, 143–152 (2001).

    Article  PubMed  Google Scholar 

  68. Hegarty, M. Spatial thinking in undergraduate science education. Spat. Cogn. Comput. 14, 142–167 (2014).

    Article  Google Scholar 

  69. Wagemans, J. et al. A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure–ground organization. Psychol. Bull. 138, 1172–1217 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Rusu, A., Fabian, A. J., Jianu, R. & Rusu, A. in 2011 15th International Conference on Information Visualisation 488–493 (IEEE, 2011).

  71. Khooshabeh, P., Hegarty, M. & Shipley, T. F. Individual differences in mental rotation: piecemeal versus holistic processing. Exp. Psychol. 60, 164–171 (2013).

    Article  PubMed  Google Scholar 

  72. Shah, P. & Miyake, A. The separability of working memory resources for spatial thinking and language processing: an individual differences approach. J. Exp. Psychol. Gen. 125, 4–27 (1996).

    Article  PubMed  Google Scholar 

  73. Gyselinck, V., Jamet, E. & Dubois, V. The role of working memory components in multimedia comprehension. Appl. Cogn. Psychol. 22, 353–374 (2008).

    Article  Google Scholar 

  74. Frick, A. Spatial transformation abilities and their relation to later mathematics performance. Psychol. Res. 83, 1465–1484 (2019).

    Article  PubMed  Google Scholar 

  75. Logie, R. H. in Psychology of Learning and Motivation vol. 42 (eds Irwin, D. E. & Ross, B. H.) 37–78 (Elsevier, 2003).

  76. Cornoldi, C. & Vecchi, T. Visuo-Spatial Working Memory and Individual Differences (Psychology Press, 2004).

  77. Prime, D. J. & Jolicoeur, P. Mental rotation requires visual short-term memory: evidence from human electric cortical activity. J. Cogn. Neurosci. 22, 2437–2446 (2010).

    Article  PubMed  Google Scholar 

  78. Mayor, R. E. (ed.) The Cambridge Handbook of Multimedia Learning (Cambridge Univ. Press, 2014).

  79. Perini, L. Diagrams in biology. Knowl. Eng. Rev. 28, 273–286 (2013).

    Article  Google Scholar 

  80. Mathewson, J. H. Visual-spatial thinking: an aspect of science overlooked by educators. Sci. Educ. 83, 33–54 (1999).

    Google Scholar 

  81. Mayer, R. E. Learning strategies for making sense out of expository text: the SOI model for guiding three cognitive processes in knowledge construction. Educ. Psychol. Rev. 8, 357–371 (1996).

    Article  Google Scholar 

  82. Mautone, P. D. & Mayer, R. E. Cognitive aids for guiding graph comprehension. J. Educ. Psychol. 99, 640–652 (2007).

    Article  Google Scholar 

  83. Healey, C. G. & Enns, J. T. Attention and visual memory in visualization and computer graphics. IEEE Trans. Vis. Comput. Graph. 18, 1170–1188 (2012).

    Article  PubMed  Google Scholar 

  84. de Koning, B. B., Tabbers, H. K., Rikers, R. M. J. P. & Paas, F. Attention guidance in learning from a complex animation: seeing is understanding? Learn. Instr. 20, 111–122 (2010).

    Article  Google Scholar 

  85. Hinze, S. R. et al. Beyond ball-and-stick: students’ processing of novel STEM visualizations. Learn. Instr. 26, 12–21 (2013).

    Article  Google Scholar 

  86. Hegarty, M., Stieff, M. & Dixon, B. in Space in Mind: Concepts for Spatial Learning and Education (eds Montello, D. R., Grossner, K. & Janelle, D. G.) 75–98 (MIT Press, 2015).

  87. Stieff, M., Hegarty, M. & Dixon, B. in Diagrammatic Representation and Inference (eds Goel, A. K., Jamnik, M. & Narayanan, N. H.) 115–127 Lecture Notes in Computer Science series vol. 6170 (Springer, 2010).

  88. Navon, D. & Margalit, B. Allocation of attention according to informativeness in visual recognition. Q. J. Exp. Psychol. Sect. A 35, 497–512 (1983).

    Article  Google Scholar 

  89. Narayanan, N. H. & Hegarty, M. On designing comprehensible interactive hypermedia manuals. Int. J. Hum.-Comput. Stud. 48, 267–301 (1998).

    Article  Google Scholar 

  90. Stieff, M., Ryu, M., Dixon, B. & Hegarty, M. The role of spatial ability and strategy preference for spatial problem solving in organic chemistry. J. Chem. Educ. 89, 854–859 (2012).

    Article  Google Scholar 

  91. Grant, E. R. & Spivey, M. J. in Diagrammatic Representation and Inference (eds Hegarty, M., Meyer, B. & Narayanan, N. H.) 236–248 Lecture Notes in Computer Science series vol. 2317 (Springer, 2002).

  92. Meirelles, I. Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations (Rockport, 2013).

  93. Castro-Alonso, J. C., Ayres, P. & Sweller, J. in Visuospatial Processing for Education in Health and Natural Sciences (ed. Castro-Alonso, J. C.) 111–143 (Springer, 2019).

  94. Shah, P. & Carpenter, P. A. Conceptual limitations in comprehending line graphs. J. Exp. Psychol. Gen. 124, 43–61 (1995).

    Article  Google Scholar 

  95. Sweller, J. Cognitive load theory and educational technology. Educ. Technol. Res. Dev. 68, 1–16 (2020).

    Article  Google Scholar 

  96. Amadieu, F., Mariné, C. & Laimay, C. The attention-guiding effect and cognitive load in the comprehension of animations. Comput. Hum. Behav. 27, 36–40 (2011).

    Article  Google Scholar 

  97. Cierniak, G., Scheiter, K. & Gerjets, P. Explaining the split-attention effect: is the reduction of extraneous cognitive load accompanied by an increase in germane cognitive load? Comput. Hum. Behav. 25, 315–324 (2009).

    Article  Google Scholar 

  98. Shah, P. & Freedman, E. G. Bar and line graph comprehension: an interaction of top-down and bottom-up processes. Top. Cogn. Sci. 3, 560–578 (2011).

    Article  PubMed  Google Scholar 

  99. Franconeri, S. L., Padilla, L. M., Shah, P., Zacks, J. M. & Hullman, J. The science of visual data communication: what works. Psychol. Sci. Public. Interest. 22, 110–161 (2021).

    Article  PubMed  Google Scholar 

  100. Lemon, K., Allen, E. B., Carver, J. C. & Bradshaw, G. L. in First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) 156–165 (IEEE, 2007).

  101. Matthew, J. S. & Michael, A. N. Gestalt and feature-intensive processing: toward a unified model of human information processing. Curr. Psychol. 21, 68–84 (2002).

    Article  Google Scholar 

  102. van Ham, F. & Rogowitz, B. Perceptual organization in user-generated graph layouts. IEEE Trans. Vis. Comput. Graph. 14, 1333–1339 (2008).

    Article  PubMed  Google Scholar 

  103. Bae, J. & Watson, B. Reinforcing visual grouping cues to communicate complex informational structure. IEEE Trans. Vis. Comput. Graph. 20, 1973–1982 (2014).

    Article  PubMed  Google Scholar 

  104. Rosli, M. H. W. & Cabrera, A. Gestalt principles in multimodal data representation. IEEE Comput. Graph. Appl. 35, 80–87 (2015).

    Article  PubMed  Google Scholar 

  105. Moreno, R. & Mayer, R. E. Cognitive principles of multimedia learning: the role of modality and contiguity. J. Educ. Psychol. 91, 358–368 (1999).

    Article  Google Scholar 

  106. Tversky, B., Zacks, J., Lee, P. & Heiser, J. in Theory and Application of Diagrams (eds Anderson, M., Cheng, P. & Haarslev, V.) 221–230 Lecture Notes in Computer Science series vol. 1889 (Springer, 2000).

  107. Matlen, B. J., Gentner, D. & Franconeri, S. L. Spatial alignment facilitates visual comparison. J. Exp. Psychol. Hum. Percept. Perform. 46, 443–457 (2020).

    Article  PubMed  Google Scholar 

  108. Wolfe, J. M. Visual search in continuous, naturalistic stimuli. Vis. Res. 34, 1187–1195 (1994).

    Article  PubMed  Google Scholar 

  109. d’Onofrio, A. et al. Maps and atlases of cancer mortality: a review of a useful tool to trigger new questions. ecancermedicalscience 10, 387 (2016).

    Google Scholar 

  110. Tversky, B. & Schiano, D. J. Perceptual and conceptual factors in distortions in memory for graphs and maps. J. Exp. Psychol. Gen. 118, 387–398 (1989).

    Article  PubMed  Google Scholar 

  111. Rock, I. Orientation and Form (Academic, 1973).

  112. Kobourov, S. G., Mchedlidze, T. & Vonessen, L. in Graph Drawing and Network Visualization (eds Di Giacomo, E. & Lubiw, A.) 558–560 Lecture Notes in Computer Science series vol. 9411 (Springer, 2015).

  113. Zacks, J., Levy, E., Tversky, B. & Schiano, D. J. Reading bar graphs: effects of extraneous depth cues and graphical context. J. Exp. Psychol. Appl. 4, 119–138 (1998).

    Article  Google Scholar 

  114. Alhadad, S. S. J. Visualizing data to support judgement, inference, and decision making in learning analytics: insights from cognitive psychology and visualization science. J. Learn. Anal. 5, 60–85 (2018).

    Google Scholar 

  115. Todd, J. T. The visual perception of 3D shape. Trends Cogn. Sci. 8, 115–121 (2004).

    Article  PubMed  Google Scholar 

  116. Brunyé, T. T., Taylor, H. A., Rapp, D. N. & Spiro, A. B. Learning procedures: the role of working memory in multimedia learning experiences. Appl. Cogn. Psychol. 20, 917–940 (2006).

    Article  Google Scholar 

  117. Brunyé, T. T., Taylor, H. A. & Rapp, D. N. Repetition and dual coding in procedural multimedia presentations. Appl. Cogn. Psychol. 22, 877–895 (2008).

    Article  Google Scholar 

  118. Dutke, S. & Rinck, M. Multimedia learning: working memory and the learning of word and picture diagrams. Learn. Instr. 16, 526–537 (2006).

    Article  Google Scholar 

  119. Huang, L., Treisman, A. & Pashler, H. Characterizing the limits of human visual awareness. Science 317, 823–825 (2007).

    Article  PubMed  Google Scholar 

  120. Thomas, A. K., Bonura, B. M., Taylor, H. A. & Brunyé, T. T. Metacognitive monitoring in visuospatial working memory. Psychol. Aging 27, 1099–1110 (2012).

    Article  PubMed  Google Scholar 

  121. Hasher, L. & Zacks, R. T. Automatic and effortful processes in memory. J. Exp. Psychol. Gen. 108, 356–388 (1979).

    Article  Google Scholar 

  122. Münzer, S., Fehringer, B. C. O. F. & Kühl, T. Specificity of mental transformations involved in understanding spatial structures. Learn. Individ. Differ. 61, 40–50 (2018).

    Article  Google Scholar 

  123. Hegarty, M. & Steinhoff, K. Individual differences in use of diagrams as external memory in mechanical reasoning. Learn. Individ. Differ. 9, 19–42 (1997).

    Article  Google Scholar 

  124. Sanchez, C. A. & Wiley, J. An examination of the seductive details effect in terms of working memory capacity. Mem. Cognit. 34, 344–355 (2006).

    Article  PubMed  Google Scholar 

  125. Kline, K. A. & Catrambone, R. Learning from multiphase diagrams: effects of spatial ability and visuospatial working memory capacity. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 55, 570–574 (2011).

    Article  Google Scholar 

  126. Brunyé, T. T. & Taylor, H. A. Working memory in developing and applying mental models from spatial descriptions. J. Mem. Lang. 58, 701–729 (2008).

    Article  Google Scholar 

  127. Deyzac, E., Logie, R. H. & Denis, M. Visuospatial working memory and the processing of spatial descriptions. Br. J. Psychol. 97, 217–243 (2006).

    Article  PubMed  Google Scholar 

  128. De Beni, R., Pazzaglia, F., Gyselinck, V. & Meneghetti, C. Visuospatial working memory and mental representation of spatial descriptions. Eur. J. Cogn. Psychol. 17, 77–95 (2005).

    Article  Google Scholar 

  129. McGrath, M. B. & Brown, J. R. Visual learning for science and engineering. IEEE Comput. Graph. Appl. 25, 56–63 (2005).

    Article  PubMed  Google Scholar 

  130. Gates, P. in STEM Education in the Junior Secondary (eds Jorgensen, R. & Larkin, K.) 169–196 (Springer, 2018).

  131. Tandon, S., Abdul-Rahman, A. & Borgo, R. Measuring effects of spatial visualization and domain on visualization task performance: a comparative study. IEEE Trans. Vis. Comput. Graph. 29, 668–578 (2023).

    PubMed  Google Scholar 

  132. Hall, K. W., Kouroupis, A., Bezerianos, A., Szafir, D. A. & Collins, C. Professional differences: a comparative study of visualization task performance and spatial ability across disciplines. IEEE Trans. Vis. Comput. Graph. 28, 654–664 (2022).

    Article  PubMed  Google Scholar 

  133. Lohse, G. L., Biolsi, K., Walker, N. & Rueter, H. H. A classification of visual representations. Commun. ACM 37, 36–50 (1994).

    Article  Google Scholar 

  134. Novick, L. R. in Diagrammatic Representation and Inference (eds Barker-Plummer, D., Cox, R. & Swoboda, N.) vol. 4045 1–11 Lecture Notes in Computer Science series vol. 4045 (Springer, 2006).

  135. Huang, W., Eades, P. & Hong, S.-H. Measuring effectiveness of graph visualizations: a cognitive load perspective. Inf. Vis. 8, 139–152 (2009).

    Article  Google Scholar 

  136. Rapp, D. N., Culpepper, S. A., Kirkby, K. & Morin, P. Fostering students’ comprehension of topographic maps. J. Geosci. Educ. 55, 5–16 (2007).

    Article  Google Scholar 

  137. Cheng, P. C.-H., Lowe, R. K. & Scaife, M. in Thinking with Diagrams (ed. Blackwell, A. F.) 79–94 (Springer, 2001).

  138. Kress, G. & van Leeuwen, T. Reading Images: The Grammar of Visual Design (Routledge, 2020).

  139. Hodgkiss, A., Gilligan, K. A., Tolmie, A. K., Thomas, M. S. C. & Farran, E. K. Spatial cognition and science achievement: the contribution of intrinsic and extrinsic spatial skills from 7 to 11 years. Br. J. Educ. Psychol. 88, 675–697 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  140. Xie, F., Zhang, L., Chen, X. & Xin, Z. Is spatial ability related to mathematical ability: a meta-analysis. Educ. Psychol. Rev. 32, 113–155 (2020).

    Article  Google Scholar 

  141. Hegarty, M., Carpenter, P. A. & Just, M. A. in Handbook of Reading Research vol. 2 (eds Barr, R., Kamil, M. L., Mosenthal, P. B. & Pearson, P. D.) 641–668 (Longman, 1991).

  142. McCrudden, M. T. & Rapp, D. N. How visual displays affect cognitive processing. Educ. Psychol. Rev. 29, 623–639 (2017).

    Article  Google Scholar 

  143. NGSS Lead States. Next Generation Science Standards: For States, By States (National Academies Press, 2013).

  144. Castro-Alonso, J. C. & Uttal, D. H. in Visuospatial Processing for Education in Health and Natural Sciences (ed. Castro-Alonso, J. C.) 53–79 (Springer, 2019).

  145. Larkin, J. H. & Simon, H. A. Why a diagram is (sometimes) worth ten thousand words. Cogn. Sci. 11, 65–100 (1987).

    Article  Google Scholar 

  146. Winn, W. Learning from maps and diagrams. Educ. Psychol. Rev. 3, 211–247 (1991).

    Article  Google Scholar 

  147. Bauer, M. I. & Johnson-Laird, P. N. How diagrams can improve reasoning. Psychol. Sci. 4, 372–378 (1993).

    Article  Google Scholar 

  148. Cheng, M. & Gilbert, J. K. in Multiple Representations in Chemical Education (eds Gilbert, J. K. & Treagust, D.) 55–73 (Springer, 2009).

  149. Scheid, J., Müller, A., Hettmannsperger, R. & Schnotz, W. Improving learners’ representational coherence ability with experiment-related representational activity tasks. Phys. Rev. Phys. Educ. Res. 15, 010142 (2019).

    Article  Google Scholar 

  150. Ainsworth, S. in Visualization: Theory and Practice in Science Education (Gilbert, J. K., Reiner, M. & Nakhleh, M.) 191–208 (Springer, 2008).

  151. Kastens, K. A., Pistolesi, L. & Passow, M. J. Analysis of spatial concepts, spatial skills and spatial representations in New York state regents earth science examinations. J. Geosci. Educ. 62, 278–289 (2014).

    Article  Google Scholar 

  152. Clark, D. et al. University students’ conceptualization and interpretation of topographic maps. Int. J. Sci. Educ. 30, 377–408 (2008).

    Article  Google Scholar 

  153. Atit, K., Weisberg, S. M., Newcombe, N. S. & Shipley, T. F. Learning to interpret topographic maps: understanding layered spatial information. Cogn. Res. Princ. Implic. 1, 2 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  154. Dong, W. et al. Using eye tracking to explore the impacts of geography courses on map-based spatial ability. Sustainability 11, 76 (2019).

    Article  Google Scholar 

  155. Cockrell, J. & Petcovic, H. L. Teaching topography using 3D printed terrain in an introductory earth science course: a pilot study. J. Geosci. Educ. 70, 2–12 (2022).

    Article  Google Scholar 

  156. McNeal, K. S. et al. A multi-institutional study of inquiry-based lab activities using the Augmented Reality Sandbox: impacts on undergraduate student learning. J. Geogr. High. Educ. 44, 85–107 (2020).

    Article  Google Scholar 

  157. Giorgis, S., Mahlen, N. & Anne, K. Instructor-led approach to integrating an Augmented Reality Sandbox into a large-enrollment introductory geoscience course for nonmajors produces no gains. J. Geosci. Educ. 65, 283–291 (2017).

    Article  Google Scholar 

  158. Carbonell-Carrera, C. & Hess-Medler, S. Interactive visualization software to improve relief interpretation skills: spatial data infrastructure geoportal versus augmented reality. Prof. Geogr. 71, 725–737 (2019).

    Article  Google Scholar 

  159. Carbonell-Carrera, C., Saorin, J. L. & Hess-Medler, S. A geospatial thinking multiyear study. Sustainability 12, 4586 (2020).

    Article  Google Scholar 

  160. Taylor, H. A., Renshaw, C. E. & Choi, E. J. The effect of multiple formats on understanding complex visual displays. J. Geosci. Educ. 52, 115–121 (2004).

    Article  Google Scholar 

  161. Carter, G., Cook, M., Park, J. C., Wiebe, E. N. & Butler, S. M. Middle grade students’ interpretations of contour maps. Sch. Sci. Math. 108, 71–79 (2008).

    Article  Google Scholar 

  162. Cid, X. C., Lopez, R. E. & Lazarus, S. M. Issues regarding student interpretation of color as a third dimension on graphical representations. J. Geosci. Educ. 57, 372–378 (2009).

    Article  Google Scholar 

  163. Hannula, K. A. Do geology field courses improve penetrative thinking? J. Geosci. Educ. 67, 143–160 (2019).

    Article  Google Scholar 

  164. Kali, Y. & Orion, N. Spatial abilities of high-school students in the perception of geologic structures. J. Res. Sci. Teach. 33, 369–391 (1996).

    Article  Google Scholar 

  165. Kreager, B. Z., LaDue, N. D., Shipley, T. F., Powell, R. D. & Hampton, B. A. Spatial skill predicts success on sequence stratigraphic interpretation. Geosphere 18, 750–761 (2022).

    Article  Google Scholar 

  166. Baker, K. M., Petcovic, H., Wisniewska, M. & Libarkin, J. Spatial signatures of mapping expertise among field geologists. Cartogr. Geogr. Inf. Sci. 39, 119–132 (2012).

    Article  Google Scholar 

  167. Atit, K., Gagnier, K. & Shipley, T. F. Student gestures aid penetrative thinking. J. Geosci. Educ. 63, 66–72 (2015).

    Article  Google Scholar 

  168. Cheek, K. A. Students’ understanding of large numbers as a key factor in their understanding of geologic time. Int. J. Sci. Math. Educ. 10, 1047–1069 (2012).

    Article  Google Scholar 

  169. Czajka, C. D. & McConnell, D. An exploratory study examining undergraduate geology students’ conceptions related to geologic time and rates. J. Geosci. Educ. 66, 231–245 (2018).

    Article  Google Scholar 

  170. Cheek, K. A., LaDue, N. D. & Shipley, T. F. Learning about spatial and temporal scale: current research, psychological processes, and classroom implications. J. Geosci. Educ. 65, 455–472 (2017).

    Article  Google Scholar 

  171. Lopez, A., Postma, A. & Bosco, A. Categorical & coordinate spatial information: can they be disentangled in sketch maps? J. Environ. Psychol. 68, 101392 (2020).

    Article  Google Scholar 

  172. Tversky, B. in The Cambridge Handbook of Visuospatial Thinking (eds Shah, P. & Miyake, A.) 1–34 (Cambridge Univ. Press, 2005).

  173. Carranza, E. J. M. Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features. Ore Geol. Rev. 35, 383–400 (2009).

    Article  Google Scholar 

  174. Provo, J., Lamar, C. & Newby, T. Using a cross section to train veterinary students to visualize anatomical structures in three dimensions. J. Res. Sci. Teach. 39, 10–34 (2002).

    Article  Google Scholar 

  175. Cohen, C. A. & Hegarty, M. Sources of difficulty in imagining cross sections of 3D objects. Proc. Annu. Mtg Cogn. Sci. Soc. vol. 29 (2007).

  176. Berney, S., Bétrancourt, M., Molinari, G. & Hoyek, N. How spatial abilities and dynamic visualizations interplay when learning functional anatomy with 3D anatomical models: interplay of spatial ability and dynamic visualization. Anat. Sci. Educ. 8, 452–462 (2015).

    Article  PubMed  Google Scholar 

  177. Nguyen, N., Mulla, A., Nelson, A. J. & Wilson, T. D. Visuospatial anatomy comprehension: the role of spatial visualization ability and problem-solving strategies: spatial anatomy task performance. Anat. Sci. Educ. 7, 280–288 (2014).

    Article  PubMed  Google Scholar 

  178. Garg, A. X., Norman, G. & Sperotable, L. How medical students learn spatial anatomy. Lancet 357, 363–364 (2001).

    Article  PubMed  Google Scholar 

  179. Khooshabeh, P. & Hegarty, M. Inferring cross-sections: when internal visualizations are more important than properties of external visualizations. Hum. Comput. Interact. 25, 119–147 (2010).

    Article  Google Scholar 

  180. Imhof, B., Scheiter, K., Edelmann, J. & Gerjets, P. How temporal and spatial aspects of presenting visualizations affect learning about locomotion patterns. Learn. Instr. 22, 193–205 (2012).

    Article  Google Scholar 

  181. Novick, L. R. & Catley, K. M. Understanding phylogenies in biology: the influence of a Gestalt perceptual principle. J. Exp. Psychol. Appl. 13, 197–223 (2007).

    Article  PubMed  Google Scholar 

  182. Novick, L. R., Shade, C. K. & Catley, K. M. Linear versus branching depictions of evolutionary history: implications for diagram design. Top. Cogn. Sci. 3, 536–559 (2011).

    Article  PubMed  Google Scholar 

  183. Novick, L. R. & Fuselier, L. C. Perception and conception in understanding evolutionary trees. Cognition 192, 104001 (2019).

    Article  PubMed  Google Scholar 

  184. Davidowitz, B. & Chittleborough, G. in Multiple Representations in Chemical Education vol. 4 (eds Gilbert, J. K. & Treagust, D.) 169–191 (Springer, 2009).

  185. Harle, M. & Towns, M. A review of spatial ability literature, its connection to chemistry, and implications for instruction. J. Chem. Educ. 88, 351–360 (2011).

    Article  Google Scholar 

  186. Stieff, M. When is a molecule three dimensional? A task-specific role for imagistic reasoning in advanced chemistry. Sci. Educ. 95, 310–336 (2011).

    Google Scholar 

  187. Risko, E. F. & Gilbert, S. J. Cognitive offloading. Trends Cogn. Sci. 20, 676–688 (2016).

    Article  PubMed  Google Scholar 

  188. Stieff, M. Mental rotation and diagrammatic reasoning in science. Learn. Instr. 17, 219–234 (2007).

    Article  Google Scholar 

  189. Stull, A. T., Hegarty, M., Dixon, B. & Stieff, M. Representational translation with concrete models in organic chemistry. Cogn. Instr. 30, 404–434 (2012).

    Article  Google Scholar 

  190. York, S., Lavi, R., Dori, Y. J. & Orgill, M. Applications of systems thinking in STEM education. J. Chem. Educ. 96, 2742–2751 (2019).

    Article  Google Scholar 

  191. McTigue, E. M. & Flowers, A. C. Science visual literacy: learners’ perceptions and knowledge of diagrams. Read. Teach. 64, 578–589 (2011).

    Article  Google Scholar 

  192. Gilbert, J. K. & Treagust, D. F. in Multiple Representations in Chemical Education vol. 4 (eds Gilbert, J. K. & Treagust, D.) 333–350 (Springer, 2009).

  193. Ivanjek, L. et al. Development of a two-tier instrument on simple electric circuits. Phys. Rev. Phys. Educ. Res. 17, 020123 (2021).

    Article  Google Scholar 

  194. Heller, P. M. & Finley, F. N. Variable uses of alternative conceptions: a case study in current electricity. J. Res. Sci. Teach. 29, 259–275 (1992).

    Article  Google Scholar 

  195. McDermott, L. C. & Shaffer, P. S. Research as a guide for curriculum development: an example from introductory electricity. part I: investigation of student understanding. Am. J. Phys. 60, 994–1003 (1992).

    Article  Google Scholar 

  196. Stetzer, M. R., van Kampen, P., Shaffer, P. S. & McDermott, L. C. New insights into student understanding of complete circuits and the conservation of current. Am. J. Phys. 81, 134–143 (2013).

    Article  Google Scholar 

  197. Hegarty, M. Mental animation: inferring motion from static displays of mechanical systems. J. Exp. Psychol. Learn. Mem. Cogn. 18, 1084–1102 (1992).

    Article  PubMed  Google Scholar 

  198. Sims, V. K. & Hegarty, M. Mental animation in the visuospatial sketchpad: evidence from dual-task studies. Mem. Cognit. 25, 321–332 (1997).

    Article  PubMed  Google Scholar 

  199. Kozhevnikov, M., Motes, M. A. & Hegarty, M. Spatial visualization in physics problem solving. Cogn. Sci. 31, 549–579 (2007).

    Article  PubMed  Google Scholar 

  200. Barniol, P. & Zavala, G. Test of understanding of vectors: a reliable multiple-choice vector concept test. Phys. Rev. Phys. Educ. Res. 10, 010121 (2014).

    Article  Google Scholar 

  201. Bollen, L., Van Kampen, P., Baily, C., Kelly, M. & De Cock, M. Student difficulties regarding symbolic and graphical representations of vector fields. Phys. Rev. Phys. Educ. Res. 13, 020109 (2017).

    Article  Google Scholar 

  202. McDermott, L. C., Rosenquist, M. L. & van Zee, E. H. Student difficulties in connecting graphs and physics: examples from kinematics. Am. J. Phys. 55, 503–513 (1987).

    Article  Google Scholar 

  203. Beichner, R. J. The impact of video motion analysis on kinematics graph interpretation skills. Am. J. Phys. 64, 1272–1277 (1996).

    Article  Google Scholar 

  204. Planinic, M., Milin-Sipus, Z., Katic, H., Susac, A. & Ivanjek, L. Comparison of student understanding of line graph slope in physics and mathematics. Int. J. Sci. Math. Educ. 10, 1393–1414 (2012).

    Article  Google Scholar 

  205. Novick, L. R. & Hurley, S. M. To matrix, network, or hierarchy: that is the question. Cognit. Psychol. 42, 158–216 (2001).

    Article  PubMed  Google Scholar 

  206. Fagnant, A. & Vlassis, J. Schematic representations in arithmetical problem solving: analysis of their impact on grade 4 students. Educ. Stud. Math. 84, 149–168 (2013).

    Article  Google Scholar 

  207. Pantziara, M., Gagatsis, A. & Elia, I. Using diagrams as tools for the solution of non-routine mathematical problems. Educ. Stud. Math. 72, 39–60 (2009).

    Article  Google Scholar 

  208. Clements, D. H., Battista, M. T., Sarama, J. & Swaminathan, S. Development of students’ spatial thinking in a unit on geometric motions and area. Elem. Sch. J. 98, 171–186 (1997).

    Article  Google Scholar 

  209. Hawes, Z., Moss, J., Caswell, B., Naqvi, S. & MacKinnon, S. Enhancing children’s spatial and numerical skills through a dynamic spatial approach to early geometry instruction: effects of a 32-week intervention. Cogn. Instr. 35, 236–264 (2017).

    Article  Google Scholar 

  210. Casey, B. M. et al. A longitudinal analysis of early spatial skills compared to arithmetic and verbal skills as predictors of fifth-grade girls’ math reasoning. Learn. Individ. Differ. 40, 90–100 (2015).

    Article  Google Scholar 

  211. Gilligan, K. A., Hodgkiss, A., Thomas, M. S. C. & Farran, E. K. The developmental relations between spatial cognition and mathematics in primary school children. Dev. Sci. 22, e12786 (2018).

    Article  Google Scholar 

  212. Hegarty, M. & Kozhevnikov, M. Types of visual–spatial representations and mathematical problem solving. J. Educ. Psychol. 91, 684–689 (1999).

    Article  Google Scholar 

  213. Newcombe, N. S., Levine, S. C. & Mix, K. S. Thinking about quantity: the intertwined development of spatial and numerical cognition. WIREs Cogn. Sci. 6, 491–505 (2015).

    Article  Google Scholar 

  214. Sella, F., Sader, E., Lolliot, S. & Cohen Kadosh, R. Basic and advanced numerical performances relate to mathematical expertise but are fully mediated by visuospatial skills. J. Exp. Psychol. Learn. Mem. Cogn. 42, 1458–1472 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  215. Bofferding, L. Negative integer understanding: characterizing first graders’ mental models. J. Res. Math. Educ. 45, 194–245 (2014).

    Article  Google Scholar 

  216. Peled, I., Mukhopadhyay, S. & Resnick, L. B. in Proc.13th Annu. Conf. Int. Group Psychol. Math. Educ. vol. 3 106–110 (1989).

  217. Gunderson, E. A., Ramirez, G., Beilock, S. L. & Levine, S. C. The relation between spatial skill and early number knowledge: the role of the linear number line. Dev. Psychol. 48, 1229–1241 (2012).

    Article  PubMed  Google Scholar 

  218. Herbst, P. Interactions with diagrams and the making of reasoned conjectures in geometry. Zentralblatt Für Didakt. Math. 36, 129–139 (2004).

    Article  Google Scholar 

  219. Chen, C.-L. & Herbst, P. The interplay among gestures, discourse, and diagrams in students’ geometrical reasoning. Educ. Stud. Math. 83, 285–307 (2013).

    Article  Google Scholar 

  220. Alsina, C. & Nelsen, R. An invitation to proofs without words. Eur. J. Pure Appl. Math. 3, 118–127 (2009).

    Google Scholar 

  221. Johnson-Laird, P. N. & Wason, P. C. Insight into a logical relation. Q. J. Exp. Psychol. 22, 49–61 (1970).

    Article  Google Scholar 

  222. Okan, Y., Garcia-Retamero, R., Galesic, M. & Cokely, E. T. When higher bars are not larger quantities: on individual differences in the use of spatial information in graph comprehension. Spat. Cogn. Comput. 12, 195–218 (2012).

    Article  Google Scholar 

  223. Trickett, S. B. & Trafton, J. G. in Diagrammatic Representation and Inference (eds Blackwell, A. F., Marriott, K. & Shimojima, A.) 372–375 Lecture Notes in Computer Science series vol. 2980 (Springer, 2004).

  224. Trickett, S. B. & Trafton, J. G. Toward a comprehensive model of graph comprehension: making the case for spatial cognition. in: Diagrammatic Representation and Inference (eds Barker-Plummer, D., Cox, R. & Swoboda, N.) 286–300 Lecture Notes in Computer Science series vol. 4045 (Springer, 2006).

  225. Huestegge, L. & Philipp, A. M. Effects of spatial compatibility on integration processes in graph comprehension. Atten. Percept. Psychophys. 73, 1903–1915 (2011).

    Article  PubMed  Google Scholar 

  226. Kozhevnikov, M., Hegarty, M. & Mayer, R. in Diagrammatic Representation and Reasoning (eds Anderson, M., Meyer, B. & Olivier, P.) 155–171 (Springer, 2002).

  227. Nolan, D. & Perrett, J. Teaching and learning data visualization: ideas and assignments. Am. Stat. 70, 260–269 (2016).

    Article  Google Scholar 

  228. Lowrie, T., Logan, T. & Hegarty, M. The influence of spatial visualization training on students’ spatial reasoning and mathematics performance. J. Cogn. Dev. 20, 729–751 (2019).

    Article  Google Scholar 

  229. Patahuddin, S. M., Rokhmah, S. & Ramful, A. What does teaching of spatial visualisation skills incur: an exploration through the visualise-predict-check heuristic. Math. Educ. Res. J. 32, 307–329 (2020).

    Article  Google Scholar 

  230. Cromley, J. G. et al. Improving students’ diagram comprehension with classroom instruction. J. Exp. Educ. 81, 511–537 (2013).

    Article  Google Scholar 

  231. Taylor, H. A. & Hutton, A. Think3d!: training spatial thinking fundamental to STEM education. Cogn. Instr. 31, 434–455 (2013).

    Article  Google Scholar 

  232. diSessa, A. A. Metarepresentation: native competence and targets for instruction. Cogn. Instr. 22, 293–331 (2004).

    Article  Google Scholar 

  233. Wason, P. C. & Shapiro, D. Natural and contrived experience in a reasoning problem. Q. J. Exp. Psychol. 23, 63–71 (1971).

    Article  Google Scholar 

  234. Gick, M. L. & Holyoak, K. J. Schema induction and analogical transfer. Cognit. Psychol. 15, 1–38 (1983).

    Article  Google Scholar 

  235. Schmidt-Weigand, F., Kohnert, A. & Glowalla, U. A closer look at split visual attention in system- and self-paced instruction in multimedia learning. Learn. Instr. 20, 100–110 (2010).

    Article  Google Scholar 

  236. Schnotz, W. & Wagner, I. Construction and elaboration of mental models through strategic conjoint processing of text and pictures. J. Educ. Psychol. 110, 850–863 (2018).

    Article  Google Scholar 

  237. Bain, K., Moon, A., Mack, M. R. & Towns, M. H. A review of research on the teaching and learning of thermodynamics at the university level. Chem. Educ. Res. Pr. 15, 320–335 (2014).

    Article  Google Scholar 

  238. Tsiganis, K. How the solar system didn’t form. Nature 528, 202–203 (2015).

    Article  PubMed  Google Scholar 

  239. Roediger, H. L. & Abel, M. The double-edged sword of memory retrieval. Nat. Rev. Psychol. 1, 708–720 (2022).

    Article  Google Scholar 

  240. Hilton, R. G. & West, A. J. Mountains, erosion and the carbon cycle. Nat. Rev. Earth Env. 1, 284–299 (2020).

    Article  Google Scholar 

  241. Lewis, S. & Maslin, M. Defining the anthropocene. Nature 519, 171–180 (2015).

    Article  PubMed  Google Scholar 

  242. Nagler-Anderson, C. Man the barrier! strategic defences in the intestinal mucosa. Nat. Rev. Immunol. 1, 59–67 (2001).

    Article  PubMed  Google Scholar 

  243. Magyar, A. et al. Synthesis of luminescent europium defects in diamond. Nat. Commun. 5, 3523 (2014).

    Article  PubMed  Google Scholar 

  244. Kornberg, H. Krebs and his trinity of cycles. Nat. Rev. Mol. Cell Biol. 1, 225–228 (2000).

    Article  PubMed  Google Scholar 

  245. Jones, R. et al. The Molecular Life of Plants (Wiley, 2013).

  246. Van Meter, P., Aleksic, M., Schwartz, A. & Garner, J. Learner-generated drawing as a strategy for learning from content area text. Contemp. Educ. Psychol. 31, 142–166 (2006).

    Article  Google Scholar 

  247. Bobek, E. & Tversky, B. Creating visual explanations improves learning. Cogn. Res. Princ. Implic. 1, 27 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  248. Fan, J. E. Drawing to learn: how producing graphical representations enhances scientific thinking. Transl. Issues Psychol. Sci. 1, 170–181 (2015).

    Article  Google Scholar 

  249. Sorby, S. Developing spatial cognitive skills among middle school students. Cogn. Process. 10, 312–315 (2009).

    Article  Google Scholar 

  250. Ainsworth, S., Prain, V. & Tytler, R. Drawing to learn in science. Science 333, 1096–1097 (2011).

    Article  PubMed  Google Scholar 

  251. Fiorella, L. & Mayer, R. E. Spontaneous spatial strategy use in learning from scientific text. Contemp. Educ. Psychol. 49, 66–79 (2017).

    Article  Google Scholar 

  252. Sorby, S. A. & Baartmans, B. J. The development and assessment of a course for enhancing the 3-D spatial visualization skills of first year engineering students. J. Eng. Educ. 89, 301–307 (2000).

    Article  Google Scholar 

  253. Veurink, N. & Sorby, S. A. in Proc. 2011 Annu. Conf. Am. Soc. Eng. Educ. 22.1210.1–22.1210.13 (2011).

  254. Wu, H.-K. & Shah, P. Exploring visuospatial thinking in chemistry learning. Sci. Educ. 88, 465–492 (2004).

    Google Scholar 

  255. Gagnier, K. M., Atit, K., Ormand, C. J. & Shipley, T. F. Comprehending 3D diagrams: sketching to support spatial reasoning. Top. Cogn. Sci. 9, 883–901 (2017).

    Article  PubMed  Google Scholar 

  256. Zhang, Q. & Fiorella, L. Learning by drawing: when is it worth the time and effort? Contemp. Educ. Psychol. 66, 101990 (2021).

    Article  Google Scholar 

  257. Zhang, Q. & Fiorella, L. Role of generated and provided visuals in supporting learning from scientific text. Contemp. Educ. Psychol. 59, 101808 (2019).

    Article  Google Scholar 

  258. Cooper, M. M., Stieff, M. & DeSutter, D. Sketching the invisible to predict the visible: from drawing to modeling in chemistry. Top. Cogn. Sci. 9, 902–920 (2017).

    Article  PubMed  Google Scholar 

  259. Wright, R., Thompson, W. L., Ganis, G., Newcombe, N. S. & Kosslyn, S. M. Training generalized spatial skills. Psychon. Bull. Rev. 15, 763–771 (2008).

    Article  PubMed  Google Scholar 

  260. Spence, I. & Feng, J. Video games and spatial cognition. Rev. Gen. Psychol. 14, 92–104 (2010).

    Article  Google Scholar 

  261. Baykal, G. E., Van Mechelen, M., Göksun, T. & Yantaç, A. E. in Proc. Conf. Creativity Making Educ. 45–54 (ACM, 2018).

  262. Lowrie, T., Logan, T. & Ramful, A. Visuospatial training improves elementary students’ mathematics performance. Br. J. Educ. Psychol. 87, 170–186 (2017).

    Article  PubMed  Google Scholar 

  263. Cheng, Y.-L. & Mix, K. S. Spatial training improves children’s mathematics ability. J. Cogn. Dev. 15, 2–11 (2014).

    Article  Google Scholar 

  264. Hawes, Z. C. K., Gilligan-Lee, K. A. & Mix, K. S. Effects of spatial training on mathematics performance: a meta-analysis. Dev. Psychol. 58, 112–137 (2022).

    Article  PubMed  Google Scholar 

  265. Martín-Gutiérrez, J. & González, M. M. A. in Visual-Spatial Ability in STEM Education (ed. Khine, M. S.) 225–239 (Springer, 2017).

  266. Newcombe, N. S. & Frick, A. Early education for spatial intelligence: why, what, and how. Mind Brain Educ. 4, 102–111 (2010).

    Article  Google Scholar 

  267. Volkwyn, T. S., Airey, J., Gregorcic, B. & Linder, C. Developing representational competence: linking real-world motion to physics concepts through graphs. Learn. Res. Pract. 6, 88–107 (2020).

    Article  Google Scholar 

  268. Firat, E. E., Joshi, A. & Laramee, R. S. VisLitE: visualization literacy and evaluation. IEEE Comput. Graph. Appl. 42, 99–107 (2022).

    Article  PubMed  Google Scholar 

  269. Börner, K., Bueckle, A. & Ginda, M. Data visualization literacy: definitions, conceptual frameworks, exercises, and assessments. Proc. Natl. Acad. Sci. USA 116, 1857–1864 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  270. Cromley, J. G. et al. Effects of three diagram instruction methods on transfer of diagram comprehension skills: the critical role of inference while learning. Learn. Instr. 26, 45–58 (2013).

    Article  Google Scholar 

  271. Resnick, I., Newcombe, N. S. & Shipley, T. F. Dealing with big numbers: representation and understanding of magnitudes outside of human experience. Cogn. Sci. 41, 1020–1041 (2017).

    Article  PubMed  Google Scholar 

  272. Jaeger, A. J., Marzano, J. A. & Shipley, T. F. When seeing what’s wrong makes you right: the effect of erroneous examples on 3D diagram learning. Appl. Cogn. Psychol. 34, 844–861 (2020).

    Article  Google Scholar 

  273. Estrella, S. in Statistics in Early Childhood and Primary Education (Leavy, A., Meletiou-Mavrotheris, M. & Paparistodemou, E.) 239–256 (Springer, 2018).

  274. Uesaka, Y., Manalo, E. & Ichikawa, S. What kinds of perceptions and daily learning behaviors promote students’ use of diagrams in mathematics problem solving? Learn. Instr. 17, 322–335 (2007).

    Article  Google Scholar 

  275. Uesaka, Y., Manalo, E. & Ichikawa, S. in Diagrammatic Representation and Inference (Goel, A., Jamnik, M. & Narayanan, N. H.) 197–211 Lecture Notes in Computer Science series vol. 6170 (Springer, 2010).

Download references

Acknowledgements

The authors thank A. Hutton for 15 years of conversations about what it means to think spatially and how to train spatial thinking in fun and engaging ways. They also thank L. A. Mason for her help with some of the figures.

Author information

Authors and Affiliations

Authors

Contributions

H.A.T. led the production of this manuscript. All authors contributed to writing the article. All authors reviewed and/or edited the manuscript before submission.

Corresponding author

Correspondence to Holly A. Taylor.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Psychology thanks Kinnari Atit, Zachary Hawes, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Taylor, H.A., Burte, H. & Renshaw, K.T. Connecting spatial thinking to STEM learning through visualizations. Nat Rev Psychol 2, 637–653 (2023). https://doi.org/10.1038/s44159-023-00224-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s44159-023-00224-6

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing